Evidence map›Paper›PMID 31903018›Full record

ArticleIEEE transactions on control systems technology : a publication of the IEEE Control Systems Society2020

System Identification Approaches For Energy Intake Estimation: Enhancing Interventions For Managing Gestational Weight Gain.

Penghong Guo, Daniel E Rivera, Jennifer S Savage, Emily E Hohman, Abigail M Pauley, Krista S Leonard, Danielle Symons Downs

Registry-linked trialAbstract read
In one paragraph

Article in IEEE transactions on control systems technology : a publication of the IEEE Control Systems Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03945266 (Control Systems Engineering for Optimizing a Prenatal Weight Gain Intervention), which is not on this map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03945266 nacompletednot on this map

Control Systems Engineering for Optimizing a Prenatal Weight Gain Intervention

TypeinterventionalSponsorPenn State UniversityRan2014 to 2018Enrolled31ConditionsOverweight and Obesity, Physical Activity, Weight Change, Body, Eating BehaviorArmsIntervention group, Control group
3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Penghong Guo
Daniel E RiveraControl Systems Engineering Laboratory (CSEL), School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ, 85281 USA.
Jennifer S SavageCenter for Childhood Obesity Research, Pennsylvania State University, University Park, PA, USA.
Emily E HohmanCenter for Childhood Obesity Research, Pennsylvania State University, University Park, PA, USA.
Abigail M PauleyExercise Psychology Laboratory, Department of Kinesiology, Pennsylvania State University, University Park, PA, USA.
Krista S LeonardExercise Psychology Laboratory, Department of Kinesiology, Pennsylvania State University, University Park, PA, USA.
Danielle Symons DownsExercise Psychology Laboratory, Department of Kinesiology, Pennsylvania State University, University Park, PA, USA.

Funding

Control Systems Engineering for Optimizing a Prenatal Weight Gain InterventionR01HL119245 · NHLBI · PENNSYLVANIA STATE UNIVERSITY, THE · PI DOWNS, DANIELLE SYMONS · 2013 to 2017
$1.8M
NHLBI NIH HHS R01 HL119245
6 · The paper itself

Abstract

Excessive maternal weight gain during pregnancy represents a major public health concern that calls for novel and effective gestational weight management interventions. In

Indexed as

intermittent measurementsKalman filterobesitysemi-physical identificationState estimationsystem identificationunderreportingweight interventions

Identifiers

PMID31903018
PMCPMC6941743

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.